The ability to follow intracellular events using a variety of protocols has opened opportunities for identifying the events associated with diseased cells, e.g., hyperplasia and neoplasticity, response to environments, e.g., drugs and other treatments, and the better understanding of the cellular pathways and their interweaving in response to a number of different conditions. By comparing normal cells with diseased cells or cells subjected to a standard environment as compared to a test environment, one can determine how the transcription profile or the proteomic profile has been changed.
In analyzing the proteome of a cell, there are many different categories of cellular components that one can measure: mRNA, proteins, protein locations, protein complexes, modified proteins, etc. Each of these may be varied, depending on the individual, the particular time of the measurement, response to various changes, such as eating, circadian rhythm, stage in proliferation, or other event that may have nothing to do with the status of interest, but may affect the cellular composition. Discovering which proteins have relevance to the cellular status is a significant enterprise. Conventional proteomics approaches that rely on two-dimensional gel electrophoresis encounter difficulties analyzing membrane-associated and low abundance proteins. Additionally, most proteomics technologies are restricted to detecting changes in protein abundance and, therefore, offer only an indirect readout of dynamics in protein activity. Numerous posttranslational forms of protein regulation, including those governed by protein-protein interactions, remain undetected. Each of these posttranslational modifications may have a prominent effect on the status of the cell, where determining only the presence of the protein may be misleading. The large numbers of proteins present in a cell, their dynamic response to changes in the status and environment of the cell, and the changes in the proteins, makes finding correlations between portions of the proteomic profile and useful information concerning disease conditions, response to drugs and useful therapeutic regimes problematic. Thus, the complete understanding of the roles that specific biomolecules play in cell physiology and pathology still presents a challenge, especially for proteins of unknown biochemical or cellular function.
The functions of certain proteins, such as adaptor or scaffolding proteins, can be gleaned from large-scale protein interaction maps generated by technologies like yeast two-hybrid, protein microarrays, and MS analysis of immunoprecipitated protein complexes. In contrast, enzymes contribute to biological processes principally through catalysis. Thus, elucidation of the activities of the many thousands of enzymes encoded by eukaryotic and prokaryotic genomes require knowledge of their endogenous substrates and products. The functional annotation of enzymes in prokaryotic systems has been facilitated by the analysis of gene clusters or operons, which correspond to sets of genes adjacently located in the genome that encode for enzymes participating in the same metabolic cascade. The assembly of eukaryotic enzymes into metabolic pathways is more problematic, however, as their corresponding genes are not, in general, physically organized into operons, but rather are scattered randomly throughout the genome.
Given the absence of a functional architecture connecting eukaryotic genomes and proteomes, the activities of their enzyme constituents are typically assessed in an empirical manner in vitro using candidate substrates and purified preparations of protein. The outcome of these “test-tube” biochemistry studies can be difficult to translate into a clear understanding of the roles that enzymes play in living systems, where these proteins are subjected to post-translational regulation and typically operate as parts of larger metabolic networks.
Development of new targets, biological pathways, and therapeutic agents would be very useful in combating various pathologies. Critical to these developments are efforts to assemble the full complement of characterized and uncharacterized enzymes encoded by the human genome into metabolic and signaling networks that contribute to complex pathologies, like cancer.
In view of the foregoing, an acute need exists to be able to accomplish the determination of endogenous catalytic activities for uncharacterized enzymes directly in living systems, for example, by the integrated application of global profiling technologies that survey both the enzymatic proteome and its primary biochemical output. Embodiments of the present invention provide such uncharacterized enzymes and methods calculated to the determination of their endogenous catalytic activities.